Multiple-phased systems, whose operational life can be partitioned into a set of disjoint periods called "phases", include several classes of systems, such as phased mission systems and scheduled maintenance systems. Because of their deployment in critical applications, the dependability modeling and analysis of multiple-phased systems is a task of primary relevance. However, the phased behavior makes the analysis of multiple-phased systems extremely complex. This paper is centered on the description and application of DEEM, a dependability modeling and evaluation tool for multiple-phased systems. DEEM supports a powerful and efficient methodology for the analytical dependability modeling and evaluation of multiple-phased systems, based on deterministic and stochastic Petri nets and on Markov regenerative processes.
DEEM: A TOOL FOR THE DEPENDABILITY MODELING AND EVALUATION OF MULTIPLE PHASED SYSTEMS / A. BONDAVALLI; S. CHIARADONNA; I. MURA; R. FILIPPINI; F. SANDRINI; S. POLI. - STAMPA. - (2000), pp. 231-236. (Intervento presentato al convegno DSN2000 INT. CONFERENCE ON DEPENDABLE SYSTEMS AND NETWORKS (FTCS-30 AND DCCA-8) tenutosi a NEW YORK) [10.1109/ICDSN.2000.857541].
DEEM: A TOOL FOR THE DEPENDABILITY MODELING AND EVALUATION OF MULTIPLE PHASED SYSTEMS
BONDAVALLI, ANDREA;
2000
Abstract
Multiple-phased systems, whose operational life can be partitioned into a set of disjoint periods called "phases", include several classes of systems, such as phased mission systems and scheduled maintenance systems. Because of their deployment in critical applications, the dependability modeling and analysis of multiple-phased systems is a task of primary relevance. However, the phased behavior makes the analysis of multiple-phased systems extremely complex. This paper is centered on the description and application of DEEM, a dependability modeling and evaluation tool for multiple-phased systems. DEEM supports a powerful and efficient methodology for the analytical dependability modeling and evaluation of multiple-phased systems, based on deterministic and stochastic Petri nets and on Markov regenerative processes.File | Dimensione | Formato | |
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